In this lecture, we introduce the use of System Dynamics Modeling (particularly, stock-and-flow simulation models) to the analysis of the spread of infectious disease. We focus our investigation around the SIR (Susceptible–Infectious–Recovered) model from epidemiology. We build up the SIR model from scratch (using a stock-and-flow model) and derive the basic reproduction number (R0) and discuss how quarantines are most practical for "flattening the curve" (the infection peak) and not totally stopping the spread of disease. We close with an introduction to other compartmental infectious disease models, such as SIS, SIRS, SEIR, SEIRS, MSEIR, and MSEIRS.
Subscribe to:
Post Comments (Atom)
Popular Posts
-
In this lecture, we review the fundamentals of numerical simulation (and Euler's method) for a simple clonal bacteria population system ...
-
In this lecture, we dig more deeply into the definition of a model and the types of models. We focus on how anything can be used as a model ...
-
In this lecture, we introduce the concepts of stochastic modeling (the use of randomness to simplify the modeling process) and chaos (the ex...
-
In this lecture, we demonstrate how to draw and simulate stock-and-flow diagrams in Insight Maker (a web-based System Dynamics Modeling (SDM...
-
In this lecture, we start to introduce "systems archetypes" as representing more complex aggregations of loops that give rise to c...
-
In this lecture, we start by reviewing numerical integration methods (Euler's method) for approximating solutions to ordinary differenti...
-
In this lecture, we introduce numerical simulation of dynamical systems (coupled ordinary differential equations) within the context of stoc...
-
We start this lecture with very brief tutorials of building, executing, and analyzing stock-and-flow diagrams in both Vensim PLE (from Venta...
-
In this lecture, we motivate the use of "causal loop diagrams" as a bridge for building system dynamics models as well as analyzin...
No comments:
Post a Comment